No abstract

Due to the extensive demand for digital images across all fields, the security of multimedia data over insecure networks is a challenging task. The majority of the existing modern encryption schemes are merely developed that ensure the confidentiality of the image data. This manuscript presents a new image encryption scheme that ensures confidentiality, user authentications, and secure key sharing among the communicating parties. Initially, the users share a secret parameter using Diffie-Hellman over the elliptic curve and pass it through SHA-256. Afterwards, the proposed scheme uses the first 128-bits for the confidentiality of the data, while the remaining 128-bits are for authentication. In the encryption algorithm, the confusion module is achieved by affine power affine transformation. At the same time, the diffusion module is attained through highly nonlinear sequences, which are generated through the elliptic curve. Experimental testing and the latest available security tools are used to verify the effectiveness of the proposed algorithm. The simulation findings and the comparison of the proposed scheme with the existing image encryption techniques reveal that the suggested scheme offers a sufficient degree of security. Furthermore, the outcome of the simulation results divulges several advantages of the proposed scheme, including a large key space, resistance to differential attacks, high efficiency, and strong statistical performance.

In current years many chaos-based Substitution boxes (S-boxes) have been proposed. Recently, an image encryption technique based on multiple chaotic S-box was offered. This encryption method was based on the concept of confusion only produced by the implementation of the S-box. The concept of confusion utilized in the understudy technique can be smashed by using just one chosen-plaintext attack and a chosen-ciphertext attack. This article presents a detailed structure of two types of cryptographic attacks on the diffusion-based encryption scheme. The proposed attacks are successfully performed to retrieve the key with very little execution time by using just one chosen image which indicates the vulnerability of multiple chaotic S-boxes-based cryptosystems. The retrieved data is passed through some statistical analysis such as correlation, histogram, and entropy to check the correctness of recovered data.

In the new era of cryptography, Substitution Boxes (S-Boxes) are very important to raise confusion in cipher text and the security of encryption directly depends on the algebraic strength of S-box. To avoid a hacker attack, researchers are focusing on creating dynamic S-boxes that are much stronger. The dominating concept for developing S-boxes is linear fractional transformation. In this article, we proposed a novel technique to generate cryptographically strong S-box by using fractional transformation based on finite field. The substitute box is constructed in two phases. Firstly, general form of dynamic fractional transformation designed which work for odd exponents in the range . The S-box is then constructed using quantic fractional transformation as an example. Secondly, in order to increase the unpredictability of proposed S-box, we use the symmetric group's S 256 permutation. The usefulness of the constructed S-box was also tested using several criteria such as nonlinearity, differential uniformity, strict avalanche criteria, linear approximation probability and bit independence criteria. To assess the reliability of S-box, its performance outcomes are compared to those of previously developed S-boxes. Furthermore, we utilized the suggested S-Box to the image encryption approach. Then, to determine the effectiveness of the encryption scheme, use several tests such as contrast, correlation, homogeneity, entropy, and energy. We have compared our results with different algorithms which ensured that the proposed strategy for ciphered image is excellent.

In many real-life problems, decision-making is reckoned as a powerful tool to manipulate the data involving imprecise and vague information. To fix the mathematical problems containing more generalized datasets, an emerging model called q-rung orthopair fuzzy soft sets offers a comprehensive framework for a number of multi-attribute decision-making (MADM) situations but this model is not capable to deal effectively with situations having bipolar soft data. In this research study, a novel hybrid model under the name of q-rung orthopair fuzzy bipolar soft set (q-ROFBSS, henceforth), an efficient bipolar soft generalization of q-rung orthopair fuzzy set model, is introduced and illustrated by an example. The proposed model is successfully tested for several significant operations like subset, complement, extended union and intersection, restricted union and intersection, the ‘AND’ operation and the ‘OR’ operation. The De Morgan’s laws are also verified for q-ROFBSSs regarding above-mentioned operations. Ultimately, two applications are investigated by using the proposed framework. In first real-life application, the selection of land for cropping the carrots and the lettuces is studied, while in second practical application, the selection of an eligible student for a scholarship is discussed. At last, a comparison of the initiated model with certain existing models, including Pythagorean and Fermatean fuzzy bipolar soft set models is provided.